Systems and methods for optically determining an acoustic signature of an object

ABSTRACT

A photo-acoustic polarimetric remote sensing apparatus includes a telescope that directs visible light photons from an object. A polarizing beam splitter is in optical alignment with the telescope. The polarizing beam splitter has first and second pathways corresponding to first and second polarization states, respectively. The first and second pathways are substantially perpendicular. A first photodetector is in optical alignment with the first pathway, and a second photodetector is in optical alignment with the second pathway. At least one processor is in communication with the first and second photodetectors. The at least one processor generates a signal corresponding to a degree of linear polarization of the photons over time, and the signal is indicative of an acoustic signature of the object.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation-in-part of U.S. application Ser. No.15/921,501, filed Mar. 14, 2018 (U.S. Pat. No. 10,228,323), which claimsthe benefit of U.S. Provisional Application No. 62/470,979, entitled,“Systems and Methods for Optically Deteiuiining an Acoustic Signature ofan Object” filed Mar. 14, 2017, the entire disclosure of which isincorporated herein by reference.

FIELD OF THE DISCLOSURE

The present disclosure is generally related to remote sensing usinglight, and in particular is directed to remote sensing usingpolarization of light to determine an acoustic signature of a remoteobject.

BACKGROUND OF THE DISCLOSURE

In the modern age of space technology, reliance on satellites issignificant and growing. The United Nations estimates that there arecurrently more than 4,000 satellites orbiting the Earth, with more than1,000 predicted to launch over the next several years. These satellitedevices have a broad span of technical uses, ranging from commercial, tocivil, to military applications. Thousands of additional space debrisobjects are in orbit as well.

Objects in geosynchronous Earth orbits (GEO) are located about 36,000kilometers away from Earth. At that distance, they represent a specialchallenge to monitor using imaging methods. Traditional means, usingEarth-based remote sensing, have generally been ineffective, even withlarge-scale apertures and expensive equipment. However, identificationand monitoring of GEO objects remains an important issue. Satelliteshave limited life-spans given the harsh environment of space, whereweathering degrades craft thermal surfaces, and the wearing ofmechanical features can lead to critical component failure. Improvedcharacterization and prediction may lead to mitigation strategies in theevent of imminent on-orbit failure. Furthermore, satelliteidentification and cross-tagging, as well as the recognition of changesin the behavior of a satellite, whether driven by phenomena internal orexternal to the satellite itself, is important in defending againstmilitary and national security threats.

Thus, a heretofore unaddressed need exists in the industry to addressthe aforementioned deficiencies and inadequacies.

SUMMARY OF THE DISCLOSURE

Embodiments of the present disclosure provide a system and apparatus forremotely sensing an object using photo-acoustic polarizationcharacteristics. Briefly described, in architecture, one embodiment ofthe apparatus, among others, can be implemented as follows. Aphoto-acoustic polarimetric remote sensing apparatus includes atelescope that directs visible light photons from an object. Apolarizing beam splitter is in optical alignment with the telescope. Thepolarizing beam splitter has first and second pathways corresponding tofirst and second polarization states, respectively. The first and secondpathways are substantially perpendicular. A first photodetector is inoptical alignment with the first pathway, and a second photodetector isin optical alignment with the second pathway. At least one processor isin communication with the first and second photodetectors. The at leastone processor generates a signal corresponding to a degree of linearpolarization of the photons over time, and the signal is indicative ofan acoustic signature of the object.

The present disclosure also provides an apparatus for remotely sensingan object using photo-acoustic polarization characteristics. Brieflydescribed, in architecture, one embodiment of the apparatus can beimplemented as follows. A photo-acoustic polarimetric remote sensingapparatus includes collection optics that direct photons. A polarizingbeam splitter has first and second pathways, where photons within thefirst and second pathways have first and second polarization states,respectively. A first optical detector is located in the first pathway,and a second optical detector is located in the second pathway. At leastone processor is in communication with the first and second opticaldetectors. The at least one processor: receives first and second signalsfrom the first and second optical detectors, respectively; calculates,for a segment of the first and second signals, a difference of the firstand second signals, a sum of the first and second signals, and a ratioof the difference to the sum; and generates, for a plurality of segmentsa signal corresponding to a sequential output of the ratio for eachsegment. The signal is indicative of an acoustic signature of an objectbeing sensed.

The present disclosure can also be viewed as providing methods ofremotely sensing an object using photo-acoustic polarizationcharacteristics. In this regard, one embodiment of such a method, amongothers, can be broadly summarized by the following steps: collectingphotons from the object; directing the photons down first and secondpathways, wherein photons within the first pathway have a firstpolarization state and photons within the second pathway have a secondpolarization state; detecting photons in the first and second pathwaysusing at least one optical detector, wherein the photons in the firstpolarization state produce a first signal and the photons in the secondpolarization state produce a second signal; receiving, with at least oneprocessor in communication with the first and second optical detectors,a first signal and a second signal; determining, with the at least oneprocessor and for a segment of the first and second signals, adifference of the first and second signals, a sum of the first andsecond signals, and a ratio of the difference to the sum; andgenerating, for a plurality of segments, a signal corresponding to asequential output of the ratio for each segment.

The present disclosure can also be viewed as providing a system andapparatus for remotely sensing an object using photo-acousticpolarization characteristics. Briefly described, in architecture, oneembodiment of the apparatus can be implemented as follows. Aphoto-acoustic polarimetric remote sensing apparatus includes collectionoptics that direct photons. An optical detector includes amicro-polarizer array located on the optical detector. Themicro-polarizer array separates the photons into at least a firstpolarization state and a second polarization state. A first portion ofthe optical detector receives the photons in the first polarizationstate, and a second portion of the optical detector receives the photonsin the at least second polarization state. At least one processor is incommunication with the optical detector. The at least one processor:receives a signal from the optical detector, wherein a first portion ofthe signal corresponds to the photons in the first polarization state,and a second portion of the signal corresponds to the photons in the atleast second polarization state; calculates, for a segment of thesignal, a difference of the first and at least second portions of thesignals, a sum of the first and at least second portions of the signals,and a ratio of the difference to the sum; and generates, for a pluralityof segments, a signal corresponding to a sequential output of the ratiofor each segment, wherein the signal is indicative of an acousticsignature of an object being sensed.

Other systems, methods, features, and advantages of the presentdisclosure will be or become apparent to one with skill in the art uponexamination of the following drawings and detailed description. It isintended that all such additional systems, methods, features, andadvantages be included within this description, be within the scope ofthe present disclosure, and be protected by the accompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the disclosure can be better understood with referenceto the following drawings. The components in the drawings are notnecessarily to scale, emphasis instead being placed upon clearlyillustrating the principles of the present disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1A is a schematic block diagram of an example of a remote sensingapparatus, in accordance with a first exemplary embodiment of thepresent invention.

FIG. 1B is a flowchart illustrating signal processing flow for signalsdetected using the remote sensing apparatus of FIG. 1A, in accordancewith the first exemplary embodiment of the present invention.

FIG. 1C is a flowchart illustrating the technical signal flow foracoustic signals processed according to FIG. 1B, in accordance with thefirst exemplary embodiment of the present invention.

FIG. 2 is a perspective illustration of the remote sensing apparatus ofFIG. 1A, in accordance with the first exemplary embodiment of thepresent invention.

FIG. 3 is a schematic illustration showing a library of acousticsignatures, in accordance with the first exemplary embodiment of thepresent invention.

FIG. 4 is a flowchart illustrating a photo-acoustic, polarimetric methodof remotely sensing an object, in accordance with the first exemplaryembodiment of the present invention;

FIG. 5 is a schematic block diagram of a remote sensing apparatus, inaccordance with a second exemplary embodiment of the present invention.

FIG. 6 is a schematic block diagram of a remote sensing apparatus, inaccordance with a third exemplary embodiment of the present invention.

FIG. 7A is a schematic block diagram of a remote sensing apparatus, inaccordance with a fourth exemplary embodiment of the present invention.

FIG. 7B is an illustration of a micro-polarizer array in use with theremote sensing apparatus of FIG. 7A, in accordance with the firstexemplary embodiment of the present invention.

FIG. 8 is a schematic block diagram showing the remote sensing apparatusof FIG. 1A with adaptive optics image correction, in accordance with thefirst exemplary embodiment of the present invention.

FIG. 9 is a schematic block diagram showing a remote sensing apparatuswith a polarization fiber switch, in accordance with a fourth exemplaryembodiment of the present invention.

DETAILED DESCRIPTION

Aspects of the invention will be further illustrated with reference tothe following specific examples. It is understood that these examplesare given by way of illustration and are not meant to limit thedisclosure or the claims to follow.

FIG. 1A is a schematic block diagram of a remote sensing apparatus 100in accordance with a first exemplary aspect of the present invention.The apparatus 100 includes collection optics 110 directing photons froman object 1. A polarizing beam splitter 120 has first and secondpathways 122 a, 122 b. Photons within the first and second pathways 122a, 122 b have first and second polarization states, respectively. Theapparatus 100 also includes a first optical detector 130 a located inthe first pathway 122 a and a second optical detector 130 b located inthe second pathway 122 b. At least one processor 140 is in communicationwith the first and second optical detectors 130 a, 130 b. The at leastone processor 140 is configured to: receive first and second signalsfrom the first and second optical detectors 130 a, 130 b, respectively;calculate, for a segment of the first and second signals, a differenceof the first and second signals, a sum of the first and second signals,and a ratio of the difference to the sum; and generate, for a pluralityof segments, a signal corresponding to the sequential output of theratio for each segment, wherein the signal is indicative of an acousticsignature of the object 1 being sensed.

The object 1 may be any remote object. For example, the object 1 may bean object 1 in space, such as a satellite, spacecraft, space station,and the like, in geosynchronous orbit. The object 1 may be an object 1within the Earth's atmosphere, such as an airplane, weather balloon,missile, and the like. The object 1 may be a remote object 1 on Earth,commonly referred to as a terrestrial object, such as a structure,building, vehicle, and the like. Multiple objects 1 may also be viewedsimultaneously or in succession, for instance, several satellites or acombination of space objects and other objects. In one example whenviewing multiple objects 1, the apparatus 100 may focus on the objects 1individually, one at a time. In another example, the apparatus 100 maydetect all objects 1 within its field of view and may separate orresolve each object 1 during analysis. In another example, the apparatus100 may focus on an atmospheric layer using conjugate planes, instead offocusing on the object 1. Focusing on an atmospheric layer may improvethe overall signal-to-noise ratio by reducing noise introduced byscintillation. In another example, the systems and methods disclosedherein may be useful in upward, downward, slanted, or lateral-lookingapplications. Such applications may include monitoring forgeo-prospecting, non-line of sight activity such as tunneling, wakeidentification, and the like. Such applications may additionally be usedto measure audible or infrasound acoustic information content fromnearby surfaces, natural or otherwise.

The photons may be from any suitable band of the electromagneticspectrum, for example, the infrared, visible, ultraviolet, or x-raybands. In use, the suitable band may be different depending on theobject 1 being sensed. For instance, if a portion or entirety of theobject 1 is optically transparent to some bands, but opticallyreflective to others, the reflective bands may be more useful indetection. As another example, if an object 1 is located in an areawhere there is no incident light from a portion of the spectrum, it maynot be useful to detect photons from that portion of the spectrum. Inone example, the apparatus 100 may include additional optical detectorsor optical detectors 130 a, 130 b capable of detecting photons inmultiple bands. Results from each band may be used to provide increasedcontrast, resolution, or detail in the final results. Depending on theimplementation of the collection optics 110 and sensors 130 a, 130 b,the apparatus 100 may receive a broad or narrow band of photons.

Collection optics 110 operate to collect photons from object 1 insufficient quantity to achieve a desired signal-to-noise performance.The collection optics 110 may be any collectors suitable to collectlight from the desired band. For example, collection optics 110 mayconstitute any known or yet to be developed telescope design, includingreflective and/or refractive optical elements. As shown in FIG. 1A, andby way of example, the collection optics 110 may be configured as aCassegrain telescope. As another example, Gregorian, modifiedDahl-Kirkham, Keplerian, or Ritchey-Chretien telescopes may be used. Thecollection optics 110 may include one or more steering optics to directthe photons to the beam splitter 120. The apparatus 100 may additionallyinclude other common optical elements, such as collimators, filters,prisms, beam sizers, and the like.

Polarizing beam splitter 120 may be any suitable polarizing beamsplitter for use with the intended spectral band. This may include cubebeam splitters, plate beam splitters, high energy beam splitters, wiregrid beam splitters, lateral displacement beam splitters, and the like.In one example, the polarizing beam splitter 120 may be a 50/50 cubebeam splitter positioned to split outgoing light by a lateral angle of90°. Light transmitted through the beam splitter 120 travels along afirst pathway 122 a to a first optical detector 130 a. Light thatreflects off the beam splitter 120 travels along a second pathway 122 bto a second optical detector 130 b. The optical detectors 130 a, 130 bmay be aligned with the pathways 122 a, 122 b such that incident lightstrikes the optical detectors 130 a, 130 b normal to the surface of theoptical detectors 130 a, 130 b. Light traveling along the first pathway122 a may have a first polarization state, while light traveling alongthe second pathway may have a second polarization state. For example,transmitted light may be P-polarized and reflected light may beS-polarized.

Separating the photons into two polarized portions provides twobenefits. First, as described in greater detail below, the presence oftwo portions allows the apparatus 100, through processing, to achievecommon mode rejection for signals subject to atmospheric scintillationor other noise-inducing phenomena. This is most common fornon-terrestrial objects, such as satellites and spacecraft. An incidentbeam that has not been split will indicate the total intensity when readby an optical detector 130 a, 130 b. However, the total intensity issubject to scintillation, the variation in the apparent brightness orposition of the object 1, which may mask or be mistaken for the acousticsignature. Therefore, rather than relying on total intensity, theapparatus 100 synchronously measures the intensities in the twoorthogonal polarization states separately. In this way, variations dueto apparent brightness or position of the object 1 can be comparedacross the first and second polarization states. Variations common toboth states may indicate scintillation, and may be discarded orotherwise not considered. Additionally, measurements using totalintensity may be highly sensitive to local vibrations in the sensingapparatus. The common mode rejection achieved by separating the beamsmay overcome this issue by allowing the apparatus 100 to discardvariations induced by vibration that are common to both states.

Second, the presence of two signals with different polarization statesallows the apparatus 100 to identify differences between the twosignals, as well as changes in the differences between the signals, todetermine characteristics of object 1, or a portion of object 1, overtime, as described in greater detail below. It will be appreciated thatchanges in the differences over time may vary, for example, in responseto vibrations of the object 1, causing a ratio of the quantities oflight in the pathways to vary. The ratio is indicative of an acousticsignature of the object 1. Such variations may be particularly presentwhere the collected photons are reflected from a man-made object.Man-made objects tend to have flat or partially flat surface structuresmade of certain materials, such that the polarization content of thelight specularly reflected from the object is indicative of the natureof the object. For example, metallic surfaces may reflect polarizedlight differently relative to the polarization state of the light. Lightin a first polarization state may be strongly reflected at certaintimes, angles, or under other conditions. Light in a second polarizationstate may be strongly reflected under different times, angles, or otherconditions. Non-metallic surfaces may behave in a similar way. Forexample, solar panels, which are common to most satellites andspacecraft, present flat surfaces that may reflect polarized lightdifferently. It may be expected that any acoustic oscillations from thesolar panels will induce change in both the angle and degree ofpolarized light reflected. The construction of beam splitter 120 isselected so that the beam splitter operates in the selected band of theelectromagnetic spectrum. For example, a polarizing beam splitter may beglass, calcite or be of a wire grid construction, although any othersuitable beam splitter may be used.

As described above, polarizing beam splitter 120 may separate the lightinto two pathways 122 a, 122 b, where the light in the first pathway 122a is linearly polarized in a first direction and the light in the secondpathway 122 b is linearly polarized in a second direction that isorthogonal to the first direction. In one example the light in eachpathway 122 a, 122 b is linearly polarized, the light being P andS-polarized, respectively. In another example, the light may beseparated according to polarization such that first pathway is polarizedto have light of a first Stokes parameter and the second pathway ispolarized to have light of a second Stokes parameter. For instance, thefirst pathway 122 a may be linearly polarized with its electric fieldaligned vertically, and the second pathway 122 b may be linearlypolarized with its electric field aligned horizontally. Alternatively,the first pathway 122 a may be linear polarized with its electric fieldaligned at 45 degrees to vertical, and the second pathway 122 b may belinearly polarized with its electric field at 45 degrees to vertical andorthogonal to the first pathway 122 a. In another example, the firstpathway 122 a may be circularly polarized in a first direction and thesecond pathway 122 b may be circularly polarized in a direction oppositeto the first direction.

In one example, the propagation of the first pathway 122 a may besubstantially perpendicular to the direction of propagation of thesecond pathway 122 b. For example, many polarizing cube beam splittersdirect the reflected beam at about a 90° angle relative to thetransmitted beam. Plate beam splitters and other reflective polarizersmay be positioned at an appropriate angle, usually about 45°, to achievea 90° beam separation as well.

First optical detector 130 a is located in the first pathway 122 a andreceives photons in the first polarization state. Second opticaldetector 130 b is located in the second pathway 122 b and receivesphotons in the second polarization state. In one example, the opticaldetectors 130 a, 130 b may be optically aligned to receive the photonsat a normal incident angle and at an optimal focal point. In anotherexample, first and/or second pathways 122 a, 122 b may also includefilter wheels, focal elements such as lenses, and other opticalcomponents. The optical detectors 130 a, 130 b may each produce a signalindicative of the quantity of photons received.

In one example, the collection optics 110 produce an image of the object1 on the first and the second optical detectors 130 a, 130 b. Theoptical detectors 130 a, 130 b may be pixelated to receive spatialinformation about pathways of the image incident thereon. Pixelateddetectors may indicate the location of the source of polarized photonsrelative to the object 1 as a whole. For example, pixelated detectorsmay indicate that a particular acoustic frequency is emanating from thetop of an object 1, which may assist in identification or verificationof operation. The optical detectors 130 a, 130 b may be any detectorssuitable to operate in the selected band or bands of the electromagneticspectrum, including CCD and CMOS devices. For instance, the opticaldetectors 130 a, 130 b may be a camera, such as a FLIR Flea® 3 CCDcamera or FLIR Grasshopper® 3 CMOS camera. In another example, thedetectors 130 a, 130 b may be other photodetectors, such as photodiodes,amplified detectors, integrating spheres, biased detectors, and thelike. In yet another example, the detectors 130 a, 130 b may bedifferent types of detectors, depending on implementation. In anotherexample, the detectors 130 a, 130 b may be identical.

In some examples, collection optics 110 collect photons from the object1 without forming an image. In those cases where an image is notgenerated or where image information is not relevant, the opticaldetectors 130 a, 130 b may operate merely to determine the quantity oflight incident on the optical detectors 130 a, 130 b. In such examples,the optical detectors 130 a, 130 b may be area detectors such as singlepixel detectors, single photon counters, or CCD/CMOS cameras thatprovide an aggregate signal rather than a pixelated signal. Thepixelated detectors may be pixelated with the light from all pixels or aportion of the pixels being integrated to determine a quantity of lightincident on the detectors.

It is to be appreciated that aspects of the present invention arevaluable even when the object 1 is not resolvable by the optical system,i.e., collection optics 110 and the optical detectors 130 a, 130 b. Inother words, the acoustic signature of the object 1 can still beobtained and characteristics of the object 1 can be determined, even ifthe optical portion of the apparatus 100 is unable to sufficientlyresolve the object 1. For example, a remote satellite or vehicle thatwould not result in a suitable visual image may still providepolarization data sufficient to resolve the acoustic signature.Furthermore, in some examples, the optical detectors 130 a, 130 b mayoperate as a photon counter, outputting a stream of numerical valuesindicative of the time of arrival of each photon incident on the opticaldetector. This may be useful in determining the acoustic properties ofthe object 1.

The first optical detector 130 a may generate a first signal, and thesecond optical detector 130 b may generate a second signal. The signalsgenerated by each optical detector 130 a, 130 b contain informationregarding the amount of light of a given polarization that is receivedfrom the object 1 at a given point in time. The signals may be generatedcontinuously at the maximum sampling rate allowed by the opticaldetectors 130 a, 130 b. The processor 140 may group signal dataaccording to time segments, or periods of duration. This may allow theapparatus 100 to easily synchronize and compare the signals. Bycalculating a difference between the first signal corresponding to aselected time segment, and the second signal corresponding to the sameselected time segment, and observing the change in the differences overtime, it is possible to gain insights into the object 1, e.g., toidentify the object, detelinine the state of operation of the objectand/or determine functions of the object. Furthermore, in one example,the difference is divided by the sum of the first signal over theselected time segment and the second signal over the same selected timesegment to provide a normalization factor. It will be appreciated that,in some examples, normalization may make the data based on thedifference more reliable by accounting for variations in the totalamount of light reflected from the object.

Although the above example was described using a difference between thefirst and second signals over a selected time segment, other operatorscomparing the first and second signals over a selected time segment maybe used to gain information regarding the quantity of light in the firstpathway and the quantity of light in the second pathway. For example, aratio of the first and second signals over a selected time segment maybe used.

The rate at which the signals are generated (i.e., the rate at whichoutputs from the first optical detector and the second optical detectorare created) may be determined at least in part by the frequency of thevibration of the object 1 to be measured. It will be appreciated that itis desirable that the rate be at least at the Nyquist rate, or theminimum rate at which a signal can be sampled without introducingerrors, which is generally twice the highest frequency present in thesignal. For example, the rate may be in the range 1 per second to 10,000per second for frequencies between 0.5 Hz and 5,000 Hz, although anysuitable rate may be used that current technology permits or thatyet-to-be produced technology may permit. For example, the rate may be1500 per second. In some embodiments, the rate is set at the photonlimit (i.e., based on the ability of the collection optics 110 tocollect photons and the ability of the optical apparatus to transmit anddetect the photons).

At least one processor 140 is in communication with the first and secondoptical detectors. In the illustrated embodiment, processor 140 iscoupled in communication with the optical detectors 130 a, 130 b. Theprocessor 140 may be any suitable computer processor for receiving andmanipulating signal data from the detectors 130 a, 130 b. For instance,the processor 140 may be commonly used computer processors such as thosehaving x86, x64, or ARM, PIC, or Arduino architecture. The apparatus 100may comprise multiple local processors 140 for additional dataprocessing or speed capabilities. The apparatus 100 may comprise adistributed network of processors 140, depending on implementation. Manyaspects of the invention may take the form of computer-executableinstructions, including algorithms executed by a programmable computer.Those skilled in the relevant art will appreciate that the invention canbe practiced with other computer system configurations as well. Certainaspects of the invention can be embodied in a special-purpose computeror data processor that is specifically programmed, configured orconstructed to perform one or more of the computer-executable algorithmsdescribed below. Accordingly, the term “computer” as generally usedherein refers to any data processor and includes Internet appliances,hand-held devices (including palm-top computers, wearable computers,cellular or mobile phones, multi-processor systems, processor-based orprogrammable consumer electronics, network computers, minicomputers) andthe like. Some aspects of the invention may also be practiced indistributed computing environments, where tasks or modules are performedby remote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules orsubroutines may be located in both local and remote memory storagedevices.

Aspects of the invention described below may be stored or distributed oncomputer-readable media, including magnetic and optically readable andremovable computer disks, fixed magnetic disks, floppy disk drive,optical disk drive, magneto-optical disk drive, magnetic tape, hard-diskdrive (HDD), solid state drive (SSD), compact flash or non-volatilememory, as well as distributed electronically over networks. Datastructures and transmissions of data particular to aspects of theinvention are also encompassed within the scope of the invention.

The processor 140 may additionally include or be in communication withcomputer-readable memory 142 and a power supply 144. The memory 142 maybe any memory suitable for signal processing, and may include both RAMand permanent storage. The power supply 144 may be any suitable powersupply, including alternating or direct current, and may be fed by awall outlet, generator, battery, photovoltaic cell, or any combinationthereof. The processor 140 may include any other necessary componentscommonly used with computers, including motherboards, housing,input/output panels, display modules, analog-to-digital converters,network connections, and the like.

The processor 140 receives the first and second signals from the firstand second optical detectors 130 a, 130 b, respectively. The processor140 is then programmed to calculate a difference of the first and secondsignals, a sum of the first and second signals, and a ratio of thedifference to the sum. These calculations may be performed for each datapoint generated by the detectors 130 a, 130 b in one example, or over aselected time segment in another example. Calculating the difference ofthe signals may give a difference in the quantity of light incident onthe first and second detectors 130 a, 130 b over that time segment.Calculating the sum of the signals may give a total of the quantity ofincident light. Calculating the ratio of the difference to the sum mayindicate the degree of linear polarization (DOLP) of the incident light.This is because the apparatus 100 has measured, independently andsimultaneously, the orthogonal polarization states as separated by thelinear polarizer. In this modality, none of the Stokes parameters arebeing directly measured. However, the change in the DOLP as a functionof time is being shown.

The first and second resultant orthogonal signals created by the opticaldetectors may be subject to a number of factors, including atmospherictransparency, inherent detector noise, the alignment angle of thepolarizer, and the maximum and minimum observed intensities.

The processor may generate a signal corresponding to a sequential outputof the ratios. Accordingly, it will be appreciated that the signal isindicative of an acoustic signature of the object. Although in theexample described above a signal is generated using a difference, otheroperators comparing the first and second signals over a selected timesegment may be used, and sequential outputs of the results of using saidoperators may be used to generate signals corresponding to an acousticsignature of the object 1.

The processor 140 may perform signal processing operations in order toprepare detected signals for further analysis. For example, commonsignal processing operations may include noise reduction, normalization,sharpening, and the like. Additional signal processing operations mayinclude processing according to Mie theory to address atmosphericscattering, and Fourier transformation to modify the domain of thecaptured signals. Mie scattering may occur as the incident light travelsthrough the atmosphere and interacts with particles with diameterssimilar to its wavelength. Mie theory may make the scattered signalsmore accurate and usable.

Additional scattering treatments may be applied, according to Rayleighscattering theory, discrete dipole approximation, and othercomputational techniques. Fourier transformation may transform thesignals into the frequency domain, allowing the processor 140 to analyzethe signals based on the frequencies present rather than the intensityof the signals. It will be appreciated that such frequency informationmay be highly indicative of the nature of the vibrations of object 1, asthe frequencies of the vibrations may correspond to acoustic frequenciesof or propagating through the object 1 itself. It will especially beappreciated that peaks in the frequency values may correspond toresonance frequencies of the object 1.

Additional techniques for time-series acoustic sampling may be employedinstead of, or in combination with, any of the above techniques. Forexample, the signals may be autocorrelated in order to discover periodicsignals, or beats, in the time domain. Time transient signals may relyon different implementations of looking at frequency distributions. Forexample, a Wigner distribution may be used to find chirp tones.Additionally, it may be useful to view played back high-speed footage atfull or decimated rates where the apparatus 1 may process and store onlysubsections of the data to conserve memory.

In one example, the signals are divided into temporal segments and atransform is performed separately on each segment, and the variations inthe frequency content of each segment are analyzed to determine changesin the acoustic signature over time. The length and number of eachsegment may be the same in one example, or may be different from segmentto segment. The length and number of each segment may depend on thesignal intensity, capture time, object size, number of frequenciespresent, and other factors. For example, a segment may have a length ofabout 256 samples or data points, and a measurement may contain about100 segments. In another example, a segment may have between 30 and100,000 samples. In another example, a measurement may contain between 1and 100 segments. More or fewer samples, and more or fewer segments maybe included, depending on the construction of the apparatus 100. Abandpass, high pass and/or low pass filter may be used to filter thesignal and eliminate or reduce frequencies known to contain excessivenoise. After the first and second signals have been compared, and theprocessor has calculated a difference, a sum, and a ratio of thedifference to the sum, the resultant data may indicate the DOLP over theselected period of time. The data may be normalized for furtheranalysis. The processor 140 may next generate a signal corresponding toa sequential output of the ratios. This signal is indicative of anacoustic signature of the object being sensed. To derive acousticsignatures from this resultant data, the processor 140 may calculatepower spectra for the resultant data stream to reveal any acousticsignal present. The power spectrum describes the distribution of powerover time into frequency components composing the signal. Peaks in thespectra may represent the frequencies of physical resonant vibrations onor from the object 1. A periodogram may be calculated for the entireduration of the signals and normalized. In one example, the periodogramsof each segment may be averaged using overlapping windows. This mayimprove the accuracy of the power determination while limiting thefrequency resolution.

Additionally, the power spectra data may be used to calculate aspectrogram of the frequencies detected as a function of time for themeasured object 1. The spectrogram may be calculated from the powerspectra of successive short sequences of the DOLP time series. In oneexample, each sequence may overlap. The spectrogram may allow a user toobserve changes in the spectral content of the DOLP signal.

Acoustic detection may be performed empirically; however, it may also beuseful to detect the activity of transient and quasi-steady signalenvironments in order to determine additional spectral components anddevelop confidence levels. The detections may be performed bygeneralized maximum and standard deviation arguments. More advancedtools, such as frequency domain decomposition, may further be used.Frequency domain decomposition (FDD) works by creating a spectral matrixand applying singular value decomposition to search for resonanceswithin the detected signals. An exemplary approach to FDD includesestimating the power spectral density matrix at discrete frequencies,performing the singular value decomposition of the power spectralintensity, then selecting any desired peaks in the power spectraldensity corresponding to mode shapes. This may enable the apparatus 100to determine the input signal characteristics of the object 1.

A tool such as FDD may allow modal analysis in regimes of low SNR withbetter performance than standard peak picking algorithms. The practicalapplications of this technique may be, in one example, that theapplication consists of measuring resolved satellites and identifyingsuch features as modal shapes of the solar panels. This information maylater be used to monitor the satellite's structural health fordangerously large resonances that could either cause structural damageor unintended orbit and attitude perturbations. The generated signal maybe output by the processor 140. In one example, the generated signal maybe stored in computer-readable memory 142 on the apparatus 100 or in aconnected database. In another example, the generated signal may beoutput digitally to a display screen, visual file, numerical entry, ortext data. In yet another example, the generated signal may be printedor otherwise indicated in hard copy format. The apparatus 100 may outputthe generated signal in any combination of formats. In another example,the apparatus 100 may compile a number of generated signals and otherrelevant data into a file, report, or other format.

In one example, where an optical detector comprises an array of pixels,the photons from object 1 or a relevant portion of object 1 may bedirected only onto a limited portion of the array. For example, such anoccurrence may result where collection optics 110 are configured toreceive photons from a set field of view, such as when the collectionoptics 110 are staring, and the object 1 moves within the field of view.In such examples, it may be advantageous if a determination of thequantity of light in a given time segment of a series is calculatedusing an output of the optical detector from only the selected segmentof the array, particularly the portion of the array receiving photonsfrom the object 1. In such examples, the segment for which the quantityof light is calculated may be movable in a manner to track the objectwithin the field of view. In other words, the object may beelectronically tracked within the field of view. In one example,electronic tracking may be used in combination with mechanical trackingusing movement of the collection optics 110. It will be appreciated thatsuch tracking may be effective in increasing the signal-to-noise of thesignal output from the processor 140.

In one example, light from a passive or natural source is incident onobject 1, which results in reflected photons from object 1 that arecollected by collection optics 110 to generate the incident light on theapparatus 100. For example, the light may be sun light, moon light, starlight or ambient light present indoors. Alternatively, remote sensingapparatus 100 may comprise one or more light sources 150 to producelight in a desired band of electromagnetic radiation that can beoperated to direct light onto object 1 to generate photons to becollected by the collection optics 110. In one example, it isadvantageous if the light source 150 is (or light sources are) pointsources; however, in one example, the light sources may be non-pointsources.

In one example, it is advantageous if a signal from processor 140(generated as described above) is output from the processor to an outputsound transducer 160 such that the remotely sensed vibrations are usedto generate a corresponding audible output. For example, such an outputtransducer may be useful where a human ear is particularly sensitive toa particular portion of the sound output or is particularly adept atidentifying a relevant sound pattern. In some cases, the frequenciesdetected may be outside of human hearing range. In one example, thesignal may be modulated—for instance, by single side-band modulation—tobring these infrasounds into the audible range by shifting thefrequencies to those suitable for human hearing.

The apparatus 100 may be partially or entirely contained in a housing(not shown). The housing may be any container, enclosure, or holdingform factor suitable to hold the apparatus 100. The collection optics110 may be located outside the housing, and may direct photons fromobject 1 into the housing and the optical system within. The componentswithin the housing may be mounted using any suitable materials andtechniques, including optical rails, mounts, tubes, epoxy, adhesive, andthe like.

FIG. 1B is a flowchart 10 illustrating signal processing flow forsignals detected using the remote sensing apparatus of FIG. 1A, inaccordance with the first exemplary embodiment of the present invention.In box 20, the first and second signals are received by the at least oneprocessor, as described relative to FIG. 1A. A number of operations maybe performed on the first and second signals to distinguish the noise inthe signals. In box 22, before substantial signal processing occurs, thesignal may be calibrated to remove bias, ensure alignment, ensure propersensitivity of the detector, and the like.

In box 30, one or more signal conditioning processes 31-37 may beapplied to the signal.

In box 31, in instances where the sample rate of the signal is wellbelow the Nyquist limit, the signal may be resampled spatially ortemporally to act as an averaging operation. This resampling may beperformed at the pixel level or in the 1-D signal. A first and secondsignal corresponding to the resampled photons may be averaged with thefirst and second signals corresponding to the photons that were firstsampled below the Nyquist limit.

In box 32, signal filtering may further improve the signal to noiseratio of the signal. Such filters may be, for example, moving averages,Savitsky-Golay filters, or Weiner deconvolution with an a priori systemtransfer function or a blind approach. These methods may, generally,reshape the signal according to the operation of the filter.

In box 33, other methods may be used to improve human perceptibility,which may include techniques such as Bayesian estimation.

In box 34, a bandpass, notch, high pass and/or low pass filter may beused to filter the signal and eliminate or reduce frequencies known tocontain excessive noise. Some exemplary applications for theseoperations may include correcting the local vibration environment of thecollection optics. If the sensor is attached to something like a drone,that has a definitive vibratory environment that is either or bothquasi-steady such as the propeller or random such as the shake fromatmospheric turbulence and if the field is moving across the sensor, thesignal will be measured differently as it moves. This will blend thelocal signal with the desired measurement from the distant vibratingsource where it may be appreciated that the separation of the measuredobject signal and the local sensor movement signal is considerablydifficult.

In box 35, a DoLP offset may be performed.

In box 36, the first and second signals may be processed using beamforming techniques. Measurements that provide spatial information fromseparate sensing apparatuses or from a pixelated focal plane may includecoherently summing or nulling separate measurements to improve thesignal estimation. Spatially separated signals will have phasedifferences, which can be measured from the timeseries modulation of thedegree of linear polarization. The phase component may be revealed bytaking the Fourier transform of the signals, which will provide a uniquemeasurement of the signal phase for spatial components in the imageplane. In beam forming applications, each of these signals may beaveraged, coherently summed to improve the signal to noise ratio, orcoherently nulled to remove unwanted acoustic sources. For stationaryapplications, the time lags from separate spatial locations computed bycross-correlation will yield scene geometry.

In box 37, feed forward, or feed back filtering operations may beperformed.

After the signal has been conditioned, vibrations may be removed. In box40, one or more vibration signal removal processes 41-45 may beperformed on the conditioned signal to counter local vibrations, eitherfrom pixelated data corresponding to the separate measurements or fromtheir respective 1-D timeseries signals. Image jitter from localvibrations to the sensor may result in a corruption of the capturedsignal.

In box 41, principal component analysis may be applied to theconditioned signals to remove spurious focal plane motion. Variablesignal components may be orthogonally transformed to locate anddetermine the values of linearly uncorrelated variables. Noisediscovered through this process may be removed from the affected signalsto yield denoised signals that may be further processed.

In box 42, measurement exclusion may be applied to the conditionedsignals.

In box 43, Kalman filtering may operate by measuring signals from anexternal accelerometer and gyroscope whose measurement axis aligns withthat of the sensor. A series of measurements observed over time maycontain image jitter noise. The resulting signal may be processed usinga Kalman filter to produce a 1-D signal estimate. The 1-D signalestimate may be subtracted from the total variational signal.

In box 44, Bayesian estimation may be applied to the signals. A Bayesestimator or decision rule may be created based on a prior distributionof one or more of the received signals. The Bayes estimator may estimatethe amount and location of noise and may cause the processor to filterthe noise based on the estimation and the received signals.

In box 45, notch filtering may be applied to remove residual vibrationalfrequencies. Other operations may include using common image fieldsources or the object source itself in a stationary application asreferences to measure quasi-steady source signals. The quasi-steadysource signals may be used to inform the frequency bands of high pass,low pass, notch, or other filters.

In box 50, the first and second signals may be further processed asdescribed relative to FIG. 1A and FIG. 4 to determine a difference, sum,and ratio of the difference to the sum of the processed first and secondsignals. Thereafter, the ratio of the signals may be processed in one ormore signal applications 61, 62, 63 according to box 60. In box 61 theratio of the signals may be directed to a technical signal output,discussed further relative to FIG. 1C. In box 62, the ratio of thesignals may be directed to an audio output as discussed relative to FIG.1A, above. In box 63, the ratio of the signals may be directed to avisual scene output as an image or video.

FIG. 1C is a flowchart 12 illustrating the technical signal flow foracoustic signals processed according to FIG. 1B, in accordance with thefirst exemplary embodiment of the present invention. FIG. 1C may beconsidered a continuation of the signal processing flow described inFIG. 1B. In box 61, signals are directed to a technical signal output.From there, one or more processes may be applied in order to manipulatethe signal data to provide technical information about the imagedobject.

In box 70, one or more frequency domain decomposition processes 71-74may be applied.

In box 71, the signal output may be expressed as a spectrogram orwaterfall plot.

In box 72, a cross-spectral density calculation may allow a user toidentify particular features from temporally separated measurements orto compare a detected signal to a known object-specific acousticspectrum. A cross-spectrum may be calculated to measure the similaritybetween pairs of acoustic spectra measured at different points in time.The amount of time difference may depend on the intended application,but in one example may be about one month. Shorter or longer timedifferences may be included within the scope of this disclosure. Whenfrequency domain signals processed by standard Fourier methods areexpressed in polar coordinates, they provide a magnitude and a phase astwo separate 1-Dimensional (1-D) vectors. The 1-D magnitude vectors maybe used to view spectral components of the frequency domain signals.

Signals may be received at a first point in time and a second point intime. The first point in time may be an earlier point, and the secondpoint may be a later point relative to the first. A difference, sum, andratio of the difference to the sum of the received signals may becalculated for signals received at the earlier point and the laterpoint. The cross-spectrum may be calculated as the earlier-determinedand later-determined frequency domain signals multiplied to make one ofthe signals the complex conjugate. The result may show anyself-similarity as spectral peaks, making an effective cross-correlationin the frequency domain. This may be compared to the result achievedwhen using the power spectrum, which may be calculated as the complexconjugate of the signal multiplied by itself. The power spectrum may beused instead, as the units of measure may be related back to thephysical issue surrounding the desired application.

In another example, this operation may be performed to the time-seriesmeasurement to calculate a cross correlation. This may indicate ifseparate sensors are not recording at the same rates. Additionally, ifthe signal is cross-correlated with itself, it will show any beatfrequencies.

The cross spectrum is a method to take frequency spectra acquired atseparate times and determine self-similarity between those acquired andtemporally separated spectra. The difference between the acquiredsignals can be seconds, minutes, months, or years and depends on thedesired application. One example, in the context of observingsatellites, may include measuring the spin rate of a spin-stabilizedbus. Spin-stabilized buses are a common architecture for broadcastsatellites manufactured by the Hughes Aircraft Company and the BoeingCompany. These architecture satellites maintain their orientation toearth by maintaining a steady angular velocity particular to a specifiedaxis while keeping the broadcasting antennae dish on a bearing whichallows a near constant earthward pointing. The torque from that spinmaintains that stable pointing position. These architecture satellitesmaintain their angular velocity by releasing propellant from a side jet.These described station keeping maneuvers occur at the discretion of thesatellite ground operators and subsequently the satellite angularvelocity and associated orbital parameters change with each stationkeeping burn.

In this example, the cross spectrum may amplify peaks in the monitoredfrequencies from temporally separated measurements. The firstinterpretation may be that if the separate spectra indicate acousticcontent and the cross spectrum lacks content, either the spacecraftvibratory environment has significantly changed or this null detectionmay indicate to the ground operator that the observations are not of thesame object. The second interpretation may be that if the separatespectra indicate acoustic content and the cross spectrum containsspectral information in the same frequency locations as the separatespectra, the ground operator may be indicated that the observations areof the same spacecraft and that the angular velocity has not changedfrom the previous measurement. The third interpretation may be that ifthe separate spectra indicate acoustic content and the cross spectrumcontains acoustic content but that the content either has significantsize or offset, the object may have performed a station keeping maneuverin the elapsed time from the previous set of measurements.

In box 73, the power spectral density of the signal may be calculated.

In box 74, the magnitude and phase spectra may be determined.

After the one or more frequency domain decomposition processes 71-74have been performed, the processed signal may optionally be tested fordata quality and SNR metrics according to box 75. In another example,one or more detection processes 81-83 may be applied to the processedsignal according to box 80. In box 81, acoustic activity may be detectedusing the processed signal. This may be performed empirically, accordingto box 82, or in an automated detection process, according to box 83.

After detection, the signal may be used in one or more technical signalapplications 91-96, according to box 90.

In box 91, the signal may be used to identify object maneuvers.

In box 92, modal imaging operations may be performed. Modes are aninherent physical property of structures determined by mass, damping,and stiffness. A mode is characterized where all parts or a subsectionfor a complex structure move sinusoidally with the same frequency andphase relation. The modes are excited by being physically driven byeither instantaneous forces or steady-source forces. Physical structuressuch as buildings, bridges, or vehicles have sets of normal modes andnatural resonant frequencies that depend on structure, material,boundary conditions, and excitation force. In practice these resonantmodes and their amplitudes may present significant design flaws that canlead to shortened mechanical lifespan or even structural collapse giventhe correct input conditions.

Modes are commonly measured by in-situ accelerometers, velocimeters, orfor smaller apparatuses, scanning laser Doppler vibrometers. Thesemeasurements may be interpreted using visual tools such as waterfallplots, spectrograms, periodograms, power spectra, or magnitude spectra.In one example, structural modes may be represented as a color-codedoverlay onto processed high-speed imaging data played at full ordecimated frame rates for visual inspection. In another example, theamplitude of the movement may be multiplied by a scale factor to themagnitude component of the returned vector from the fast Fouriertransform. In processed high-speed imaging, the movement is spatiallyamplified for visual inspection.

In the present disclosure, the processed signal may be further processedto discover the modes present within an imaged object. Modal processingtechniques may measure individual spatial locations to have frequencyand phase components in equal relation to separate simultaneous spatiallocation measurements for a given surface or structure. In practice,each pixel for each image may be processed as a timeseries vector, whichmay then be processed as a fast Fourier transform (FFT). From this, theoutput would be a 3-Dimensional array of returned FFT vectors for eachpixel for each frame. A generalized peak picking algorithm based onheuristic noise thresholds or frequency domain decomposition mayidentify pixels with self-similarity in both time and space in the FFTarray. Self-similarity may be indicated by the received data from agroup of pixels existing within an acceptable threshold with both thesame frequency and phase component over a period of time. Discoveredmodes may be indicated by generating an additional signal correspondingto the discovered modes. The additional signal may be displayed visuallyas false-color enhancement, motion amplification, or any combinationthereof to display post processed image data at either the full or adecimated rate. In specific circumstances and with appropriateinformation the technique may measure out of plane displacement ofstructures or surfaces, material properties may be estimated such as thestiffness or damping coefficients, or input forces as approximatedmeasurements. It may also be recognized that in specific settings with awell approximated physical model, the effective mass may also beestimated. As an example this technique may measure such instances asthe normal modes of a car engine as seen from the vehicle body, abuilding's modes, or an aircraft wing's modes for inspection.

In the illustrative example of observing satellites it may beappreciated that many key operating parameters may be estimated frommeasuring vibration spectra indicative of a maneuver event if observedand identified for the full event duration. Among these parameters aremass flow rate, fuel consumption, and specific impulse. These parametersmay fully be estimated with an a priori object mass estimate, a knowndelta-v magnitude, and a known direction as observed from the remoteacoustic sensor. A unique vibration spectrum, if observed on aspacecraft during a maneuver, will provide the necessary time resolutionto accurately estimate the beginning and end of a maneuver and thusprovide an accurate event duration. This allows estimations of both thework performed and impulse imparted. The innovative step for accurateevent duration would allow faster than the currently used angles-onlymethod for maneuver detection.

As described above, a post-processed cube may display backwards asfalse-colored video at full or decimated rates or as motion amplifiedvideo. Denoising and frequency filtering techniques may be applied toremove unwanted sources in the field or sharpen the signal. Incontrolled environments where a priori forces and scene geometry areknown, standard vibratory analysis may be applied where the motion ofstructures or surfaces may be measured as surface displacement, thestructural stiffness may be estimated, the excitation force may beestimated, or separate material properties may be estimated. In caseswhere the input force is known and the stiffness and dampeningcoefficients are well-approximated, the effective mass may be estimatedby assuming that the object moves according to a set of linearequations.

In box 93, the acoustic measurements provided by a pixelated opticaldetector may provide information useful for imaging through obscurantssuch as clouds, dust, smog, and haze. For pixelated focal planes wherespatial information is available and each pixel in the plane representsa unique timeseries measurement, an obscurant cloud may be vibrated by asource 1 hidden behind the obscurant. The obscurant may be removed fromthe imaging data by measuring a vibration signature of each pixel of theat least one optical detector. The resulting Fourier power componentsmay be removed by using one or more differencing techniques. A signalcorresponding to the acoustic signature may be generated, revealing thevibrating source behind the obscurant. The generated signal may resultfrom taking the measured signal into the frequency space, differencingthe identified peaks, and taking an inverse fast Fourier transform. Inpractical use, the differencing or nulling operation may be performed inthe frequency domain, then an inverse Fourier transform is performed.

In box 94, beam forming techniques may be used to identify scenegeometry of the detected object.

In box 95, object recognition techniques may be used to identify theobject.

In box 96, property identification techniques may be used to identifyproperties or physical characteristics of the detected object.

Additional signal processing and technical signal output paths arecontemplated within the scope of this invention. For example, any of thefrequency domain operations performed using Fourier transforms mayalternatively be performed using wavelet calculations.

Operating Example

The following operating example is given to provide additional detail ofthe processes of FIGS. 1B, 1C used with FIG. 1A.

A user may record the two or more separate and simultaneouspolarizations from an object using the collection optics, such as atelescope. If the bandwidth of the frequency signal being sought afteris unknown such as a common car hood for lateral applications or asatellite for upward looking applications, the user may use asufficiently fast sampling rate while maintaining a sufficient photonsampling per the detector. The user may want to detect a large number ofphotons to overcome the fundamental errors in the measurement where anexample of an error could be intrinsic shot noise. The quality of theacquired DoLP polarization signal may then depend on the angle ofillumination, the driving force and surface displacement, and thematerial properties of the object.

A first step for processing the data may be the DC removal from thesignal. This DC removal step may include either a full frame DCsubtraction for pixelated detectors or an average measurementsubtraction for single cell detectors. For applications relying on theuse of pixelated focal planes, the user may then remove field dependentresponse errors. These response errors may be the result of sensormanufacturing error, optical field curvature, field dependenttransmission differences, and the like. These response errors may beremoved by such a process as the division of a flat field measurementfrom the acquired data or a like irregularity removal process.

A second step of data processing may be the resampling of the signal,the necessity of which may be determined by the acquired acousticcontent. The need for resampling may be based upon the location of thefrequency content in relation to the full measurement bandwidth. The actof resampling provides several advantages to the user, those being areduction in the extent of pink noise, and an improvement in the signalby averaging temporally the acquired data. For applications withsufficiently high sampling rates, the digitization of the recordedsignal may be improved beyond the limitations imposed by the sensor.

For those skilled in the art, it may be appreciated that each of theprocessing steps are linear operations allowing the operations to becarried out without regard for their order. The acquired signal may thenif necessary, be improved by removing the local vibration signal fromthe total acquired signal. These removal processes may encompass theprocesses found in boxes 41-45 and may depend on the quality of theacquired data.

The signal may then be improved in terms of noise content. In the idealmeasurement environment, a system transfer function may be known prioror be acquired from the object. From this system transfer function,deconvolution may produce a sufficiently restored signal. Otherapproaches to restoration may be such approaches as blind deconvolution,Savitsky-Golay filters at the expense of nulling higher frequencycontent, or normalizing the signal to standard metrics such as the mean.Additional processing steps may include the coherent summing ofmeasurements from beam forming, the perceptibility improvement withBayes methods, bandpass and notch filtering, feed filters, and delayingsamples to create an effective derivative filter. The delay of samplesmay improve the signal to noise ratio for higher frequency content bycreating an effective derivative filter without sacrificing signalbandwidth. These conditioning processes may encompass the processesfound in boxes 32-37 and may depend on the quality of data acquired anda priori information available to the user.

The signal after being sufficiently processed may be used for eithervisual interpretation with either the full, decimated, or singleinstances of the acquired data. Other uses may include converting theoptical measurement into audio for interpretation; the last use may alsobe continuing to use the signal for technical applications. These signaluses may encompass the processes found in boxes 61-63 and may depend onthe user application.

The technical applications of the data may include the visualization ofthe acquired data using frequency space visualization tools. These toolsmay be those described in processes 71-74 and may depend on theapplication for the user. The visualization of the time domain signalsmay include 1-dimensional timeseries plots of the signal or the playbackof imaging or video data. The later applications of the technical datamay include detecting significant features from the data using librariesand correlation, a machine learning framework, or empirically. Thesetools may be those described in processes 81-83 and FIG. 3. The user maythen use the automatically or empirically generated features of thesignal to perform modal analysis, estimations of spacecraft parameters,object recognition, or material and property identification. Thesesignal uses may encompass the processes 91-96 and may depend on the userapplication.

FIG. 2 is a perspective illustration of the remote sensing apparatus 200of FIGS. 1A-1B. FIG. 2 shows an exemplary implementation of the opticalsystem of the apparatus 200, including collection optics 210, directingoptics 260, focusing elements 262, 264 a, 264 b, beam splitter 220, andoptical detectors 230 a, 230 b. In this example, the collection optics210 are of a Cassegrain design and operate to direct photons todirecting optics 260, which are shown as a mirror. In another example,directing optics 260 may be a prism or other elements suitable fororienting the apparatus 200 in a desired direction. The directing optics260 direct the photons into a first focusing element 262, whichcollimates the incident beam of light before it reaches the beamsplitter 220. The first focusing element 262 may be any suitable lens orcombination of elements suitable to collimate light in the desired bandof the electromagnetic spectrum. The beam splitter 220 divides the lightinto two pathways where the light in each pathway is linearly polarizedand the linear polarizations are orthogonal to one another (i.e., thepathways are p and s polarized, respectively). Second and third focusingelements 264 a, 264 b, respectively, focus the light from each pathwayonto the optical detectors 230 a, 230 b, respectively.

FIG. 3 is a schematic illustration showing a library 300 of acousticsignatures. In one example, it may be advantageous to have a library 300of acoustic signatures with which a signal output 310 from the processor340 can be compared, e.g., by performing a correlation calculation. Thelibrary 300 may include acoustic signatures for known objects, such assatellites, spacecraft, vehicles, and the like. The library 300 mayinclude acoustic signatures for known objects in known environments,such as in space, high altitude, inclement weather, and the like. Thelibrary 300 may include a collection of acoustic signatures for knownactivities, such as the operation of a mechanical piece or extension ofsolar panels. The activities may be further categorized based on whetherthey are running normally, i.e., the components are functioning well, orrunning abnormally, i.e., a component may be failing or functioningimproperly. The library 300 may include only partial acoustic signaturesas well. In one example, the library 300 may be comprised of entries370, where each entry is the signal output from processor 140 of theremote sensing apparatus 100 when it is receiving light from a knownobject in a known state (i.e., it is the acoustic signature of a knownobject 1 operating in a known manner). The entries may be stored asdigital files on computer-readable memory 342 which may be the on-boardmemory of the apparatus 100 relative to FIG. 1A, or a connecteddatabase.

The database may be connected locally or remotely by a network system.The processor 340 may be programmed to compare the signal output 310with the library entries 370. The comparison may utilize machinelearning, deep learning, neural networks, or other computationaltechniques to find signal patterns that match. Comparisons of thisnature may use the database entries 370 to train the processor 340 whichfactors are indicative of certain objects, environments, activities, andthe like. In one example, one or more machine learning techniques, suchas principal component analysis, may be used. In another example, theentries 370 may be converted into audio fingerprints, where thedata-heavy digital frequency information is converted intoeasy-to-search numeric and hash values. These numeric and hash valuesmay be normalized and compared against the signal output 310 to detectmatching values or patterns of values. In one example, t-distributedstochastic neighbor embedding (t-SNE) may be used. It will beappreciated that information regarding an unknown object could bedetermined when there is a correlation between the acoustic signature inthe library 300 and a signal from the processor 140 when it is observingthe unknown object. The processor 140 may compare the library entries370 directly, or it may convert the unknown data into audio fingerprintsfor faster searching. The comparison may be performed contemporaneouslywith the signal acquisition, i.e., as the apparatus 100 is collectingthe photons. In another example, the comparison may be performed afterthe entire signal 310 has been captured and processed. Other statisticaltools, such as probabilistic graphical models, may be used.

This framework may be useful in a number of instances. For example, inthe application of identifying non-resolved spacecraft, ground operatorsmay need to identify and characterize several objects or spacecraft in alimited timespan while relying on the acquired acoustic spectra. Fromthese many measurements the implementation of probabilistic graphicalmodels (PGMS) may allow the computer to make decisions on limitedamounts of data, in contrast to other computational approaches such asneural networks. The ground operator may then rely on the output of thePGM to decide or assist in the identification and characterization ofrelevant aspects of the spacecraft. Those decisions may have a developedconfidence interval. These decisions may provide such useful informationto the ground operator as the satellite architecture, object specificID, and subsystem activity among the other described aspects of theinvention. The PGM approach is useful because the model of data that theprobabilities are calculated from may be idealized calculations basedupon the physical principles of the source interaction. In the continuedsatellite example, these realized models may be such instances as theoutputs of finite element analysis models, satellite reflectance models,and the like. This proves beneficial because the data to dictatedecisions may be modelled and simulated whereas neural net methods mayrequire large amounts of acquired data to be accurate.

FIG. 4 is a flowchart 400 illustrating a photo-acoustic, polarimetricmethod of remotely sensing an object, in accordance with the firstexemplary embodiment of the present invention. It should be noted thatany process descriptions or blocks in flow charts should be understoodas representing modules, segments, portions of code, or steps thatinclude one or more instructions for implementing specific logicalfunctions in the process, and alternate implementations are includedwithin the scope of the present disclosure in which functions may beexecuted out of order from that shown or discussed, includingsubstantially concurrently or in reverse order, depending on thefunctionality involved, as would be understood by those reasonablyskilled in the art of the present disclosure.

Step 410 includes collecting photons from the object. The collectionoptics 110 may be those discussed relative to FIG. 1A, such asreflective or refractive telescopes, zoom lenses, or other optics.

Step 420 includes directing the photons down first and second pathways,wherein photons within the first pathway have a first polarization stateand photons within the second pathway have a second polarization state.The input beam may be split by one or more polarizing beam splitters,beam splitting plates, birefringent glass, prisms, and the like. Theangular deviation between the first and second pathways may be anysuitable deviation necessary to separately detect the first and secondpathways. For instance, when certain prisms are used, as will bediscussed further in FIG. 5, below, the angular deviation may be small,up to several degrees. When a polarizing beam splitting cube is used,the angular deviation may be much greater, up to about 90° or more. Theproper angular deviation may depend on the optical system design.

Step 430 includes detecting photons in the first and second pathwaysusing at least one optical detector, wherein the photons in the firstpolarization state produce a first signal and the photons in the secondpolarization state produce a second signal. In one example, a singleoptical detector may be used to detect both the first and secondpathways. The photons in the pathways, may strike different portions ofthe optical detector, allowing the detected signals to be calculatedindependently. In another example, multiple detectors may be used. Forinstance, one detector may be placed in each pathway to detect theincident light separately. In one example, more than two detectors maybe used to create spatial separation in the detected data.

Step 440 includes receiving, with at least one processor incommunication with the at least one optical detector, a first signal anda second signal corresponding to the photons in the first and secondpathways, respectively.

Step 450 includes determining, with the at least one processor and for asegment of the first and second signals, a difference or the first andsecond signals, a sum of the first and second signals, and a ratio ofthe difference to the sum. Where the first and second signals both comefrom a single optical detector, the signals may need to be separated bythe processor before the determinations can be made. Separation maysimply include recording values in different areas or different pixelson the optical detector separately. In one example, separation mayrequire noise reduction operations to ensure that the signal data istruly separate, especially at the part of the optical detector where thetwo pathways hit nearest each other. Additional signal processing, asdiscussed relative to FIG. 1A, above, may be performed by the processor.

Step 460 includes generating a signal for a plurality of segmentscorresponding to a sequential output of the ratio for each segment,wherein the signal is indicative of an acoustic signature of the object.The generated signal may be the signal discussed relative to FIG. 1A,above, and may be useful as an acoustic indicator of the nature,operation, or state of the object being sensed.

The method may further include any other features, components, orfunctions disclosed relative to any other figure of this disclosure.

FIG. 5 is a schematic block diagram of a remote sensing apparatus 500 inaccordance with a second exemplary aspect of the present invention. Theapparatus 500 includes collection optics 510 directing photons from anobject 1. A polarizing prism 520 angularly separates the photons into afirst polarization state 522 a and a second polarization state 522 b. Anoptical detector 530 is included. A first portion of the opticaldetector 530 receives the photons in the first polarization state 522 a,and a second portion of the optical detector 530 receives the photons inthe second polarization state 522 b. At least one processor 540 is incommunication with the optical detector 530. The at least one processor540: receives a signal from the optical detector 530, wherein a firstportion of the signal corresponds to the photons in the firstpolarization state 522 a, and a second portion of the signal correspondsto the photons in the second polarization state 522 b; calculates, for asegment of the first and second signals, a difference of the first andsecond portions of the signals, a sum of the first and second portionsof the signals, and a ratio of the difference to the sum; and generates,for a plurality of segments, a signal 550 corresponding to a sequentialoutput of the ratio for each segment. The signal is indicative of anacoustic signature of an object 1 being sensed.

Many aspects of the optical system of apparatus 500 may be the same orsimilar to those discussed relative to FIGS. 1 and 2, above. Forinstance, the collection optics 510, the optical detector 530, and theother optical elements such as directing optics and focusing optics (notshown) may be used. The collection optics may direct photons from object1 into the rest of the apparatus 500.

The photons may be directed to a polarizing prism 520. The polarizingprism 520 may angularly separate the incident photon beam into two beamshaving two different polarization states. The polarizing prism 520 maybe any suitable birefringent polarizers, such as Glan-Taylor polarizers,Glan-Thompson polarizers, Wollaston prisms, Rochon prisms, and the like.By way of example, Wollaston prisms may provide a symmetric deviationbetween the first and second beams while maintaining substantially equalintensities across both beams. In one example, multiple prisms 520 maybe used to separate the beams, separate the polarization states,equalize the beam intensities, or direct the beam path.

The photon beam may be separated into photons in a first polarizationstate 522 a and a second polarization state 522 b. The photons from thefirst polarization state 522 a may be linearly polarized and orthogonalto the photons from the second polarization state 522 b. In one example,the photons may be circularly or elliptically polarized by introductionof a quarter wave plate. The photons from both states 522 a, 522 b mayhit the optical detector 530 along different portions of the detectorsurface. A first portion of the optical detector 530 may receive thephotons from the first state 522 a, and a second portion of the opticaldetector 530 may receive the photons from the second state 522 b. In oneexample, the signals created by the first and second polarization states522 a, 522 b may be individually resolvable due to the angularseparation of the photons in the first and second polarization states522 a, 522 b. In another example signal processing may be required toseparate a portion of the signals.

The at least one processor 540 may be any of the processors andaccompanying components 542, 544 as discussed relative to FIG. 1A,above. The processor 540 may receive a signal from the optical detector530, wherein a first portion of the signal corresponds to the photons inthe first polarization state 522 a, and a second portion of the signalcorresponds to the photons in the second polarization state 522 b. Thefirst and second portions of the signal may correspond with the numberor intensity of photons incident upon the optical detector 530 relativeto the first and second polarization states 522 a, 522 b. The processor540 may calculate a difference of the first and second portions of thesignals, a sum of the first and second portions of the signals, and aratio of the difference to the sum. This operation may be similar to thecalculation performed relative to FIG. 1A, above. The processor 540 maygenerate a signal 550 corresponding to a sequential output of theratios. The signal 550 may directly express the degree of polarizationof the input photons, and may vary in magnitude over time. As discussedabove, the variations in magnitude over time may be transformed orotherwise used to determine oscillating frequencies coming from theobject 1. These frequencies can be used to create an acoustic signatureof the object 1. The signal 550 may be further processed to make iteasier to hear, to filter noise, or to focus on particular frequenciespresent. The signal 550 may be fed to an acoustic transducer, output toa screen, report, or other file, or compared against a library ofentries as discussed in FIG. 3.

In one example, the apparatus 500 may include a flip mirror 524 that canbe moved into and out of the beam path before the photons reach thepolarizing prism 520. The flip mirror 524 may be used to direct theincoming photons to an acquisition detector 532. The acquisitiondetector 532 may be an optical detector as discussed relative to FIG.1A, including a CCD or CMOS camera. It may be in communication with theprocessor 540. The acquisition detector 532 may be used to locate orfocus in on the object 1. This may be especially helpful when thedesired imaging band is in the visible spectrum. The image provided bythe acquisition detector may allow a user to align the apparatus 500 orto track the object 1. In one example, the image data may not beconsidered by the processor 540 in the acoustic signature calculationsbelow. In another example, the image data may be used as a visualoverlay to show, spatially, where measured frequencies originated fromon the object 1. The acquisition detector may additionally be used withthe other aspects of this disclosure.

In another example, the apparatus 500 may further include anaccelerometer 546. The accelerometer 546 may provide 3-axis motion anddirectional data relative to the position and movement of the apparatus500. The accelerometer 546 may be in communication with the processor540, which may provide the data to a user. In one example, movement ofthe apparatus 500 may be controlled by a computerized motor, such as astepper motor, capable of tracking GEO objects as they travel across thesky. The data from the accelerometer 546 may allow the motor to maintainan accurate tracking position.

FIG. 6 is a schematic block diagram of a remote sensing apparatus 600,in accordance with a third exemplary embodiment of the presentinvention. The apparatus 600 may remotely detect the modulation ofcircularly polarized light incident upon the apparatus 600. Theapparatus 600 may include collection optics 610 to collect and receivephotons from an object 1.

The collection optics 610 may direct light from the object 1 down anoptical path. In one example, the light is split by a 50/50 beamsplitter 620 that divides the light into two pathways 622 a, 622 b ofapproximately equal intensity. The light may not be polarized at thistime. The light in each pathway 622 a, 622 b may further be directedthrough respective quarter waveplates 630 a, 630 b and then throughrespective linear polarizers 640 a, 640 b. The quarter waveplates 630 a,630 b and linear polarizers 640 a, 640 b may be selected to separate thelight in the pathways 622 a, 622 b into left and right circularlypolarized light. For example, light in the first pathway 622 a may beleft circularly polarized, while light in the second pathway 622 b maybe right circularly polarized. The 50/50 beamsplitter 620 may be anysuitable plate, circular filter, tube, cube, or the like for dividinglight into two distinct pathways. The quarter waveplates 630 a, 630 band linear polarizers 640 a, 640 b may be any suitable quarterwaveplates and linear polarizers commonly used, depending on thespectrum of light being detected.

Circularly polarized light from pathways 622 a, 622 b may hitphotodetectors 650 a, 650 b, respectively, located in the pathways. Thephotodetectors 650 a, 650 b may be in communication with a processor 660as described above relative to FIGS. 1 and 5. The photodetectors 650 a,650 b may communicate first and second signals to the processor 660 aslight is detected. The processor 660 may include computer memory, powersupply, and other electronic components as shown in FIG. 1A. Theprocessor 660 may calculate a difference of the first and secondsignals, a sum of the first and second signals, and a ratio of thedifference to the sum. This operation may be similar to the calculationperformed relative to FIG. 1A, above. The processor 660 may generate asignal corresponding to a sequential output of the ratios. The signalmay directly express the degree of polarization of the input photons,and may vary in magnitude over time. As discussed above, the variationsin magnitude over time may be transformed or otherwise used to determineoscillating frequencies coming from the object 1. These frequencies canbe used to create an acoustic signature of the object 1. The signal maybe further processed to make it easier to hear, to filter noise, or tofocus on particular frequencies present. The signal may be fed to anacoustic transducer, output to a screen, report, or other file, orcompared against a library of entries as discussed in FIG. 3.

FIG. 7A is a schematic block diagram of a remote sensing apparatus 700,in accordance with a fourth exemplary embodiment of the presentinvention. The apparatus 700 includes collection optics 110 directingphotons from an object 1. A micro-polarizer array 720 is located on anoptical detector 730. Photons propagating through the micro-polarizerarray 720 have at least first and second pathways 722 a, 722 b. Photonswithin the at least first and second pathways 722 a, 722 b have at leastfirst and second polarization states, respectively. The optical detector730 is located in the first and second pathways. At least one processor140 is in communication with the optical detector 730. The at least oneprocessor 140 is configured to: receive a signal from the opticaldetector 730, wherein a first portion of the signal corresponds to thephotons in the first polarization state, and a second portion of thesignal corresponds to the photons in the at least second polarizationstate; calculate, for a segment of the signal, a difference of the firstand at least second signals, a sum of the first and at least secondsignals, and a ratio of the difference to the sum; and generate, for aplurality of segments, a signal corresponding to the sequential outputof the ratio for each segment, wherein the signal is indicative of anacoustic signature of the object 1 being sensed.

The micro-polarizer array 720 may be any array of polarizing elements.The micro-polarizer array 720 is located on the optical detector 730.For purposes of illustration, the micro-polarizer array 720 is shownspaced apart from the optical detector 730. This is done to illustratethat the photons that pass through different portions of the array maybe divided into different states of polarization. However, in practice,the polarizing elements will be located on and part of the opticaldetector 730.

The processor 140 may additionally include or be in communication withcomputer-readable memory 142 and a power supply 144. The memory 142 maybe any memory suitable for signal processing, and may include both RAMand permanent storage. The power supply 144 may be any suitable powersupply, including alternating or direct current, and may be fed by awall outlet, generator, battery, photovoltaic cell, or any combinationthereof. The processor 140 may include any other necessary componentscommonly used with computers, including motherboards, housing,input/output panels, display modules, analog-to-digital converters,network connections, and the like.

The apparatus 700 may include an artificial light source to illuminatethe object 1 as shown in FIG. 1A.

FIG. 7B is an illustration of a micro-polarizer array 720 in use withthe remote sensing apparatus 700 of FIG. 7A, in accordance with thefourth exemplary embodiment of the present invention. Themicro-polarizer array 720 may include a plurality of polarizers 770,771, 772, 773 located in the path of individual pixels 724, 725, 726,727 of the optical detector 730. One polarizer may be located in frontof one pixel—for instance, polarizer 770 may be located in front ofpixel 724, polarizer 771 in front of pixel 725, and so on, asillustrated in FIG. 7B. Four pixels are shown in FIG. 7B as an exampleonly. In practice, an optical detector 730 may include millions ofpixels, each with their own micro-polarizer. In the example shown, eachpixel 724, 725, 726, 727 includes a linear polarizer 770, 771, 772, and773 at 0°, 45°, 90°, and 135°. Other micro-polarizer arrays may includefewer polarizing elements, for example, at two angles of linearpolarization. In one example, the micro-polarizer array 720 may be theSony® Pregius IMX250MZR Polarization sensor. Photons propagating throughthe micro-polarizer array and onto the optical detector 730 areseparated into their component linear polarization states at each pixel.This may allow the polarization of light incident on the opticaldetector 730 to be measured without the use of beamsplitters or prisms,which in turn allows the apparatus 700 to be simpler and more compact.

The micro-polarizer orientations are fixed, meaning only one state ofpolarization can be measured for each single pixel. But for a camerawith a large number of pixels, it is possible to get many measurementsand many states. For the purpose of the DoLP calculation, orthogonalpixel axes may be selected for calculations. These may be interpolateddown to a DoLP image and further processed, or processed as is. In orderto modulate the polarization angle with time, a polarization fiberswitch implementation, described relative to FIG. 9 below, may benecessary.

FIG. 8 is a schematic block diagram showing the remote sensing apparatus801 of FIG. 1A with adaptive optics image correction, in accordance withthe first exemplary embodiment of the present invention. Adaptive opticsmay be effective for both upward and horizontal path imaging scenariossuch as those employed by free space optical communications systems,astronomical telescopes, and directed energy systems. Passive approachesto image restoration for the improvement in measuring the intensity of asurface may be achieved by the use of image deconvolution, eitherthrough blind approaches, or as informed by additional wavefrontmeasurements, as discussed above. Active approaches to image restorationfor the improvement in measuring the intensity of a surface may includethe use of an adaptive optics system. As an object 1 is imaged bycollection optics 810, photons from the object 1 may be subject toatmospheric distortion 870 or other conditions that alter the appearanceof the object 1. As a result, the imaged signal may be distortedproportional to the degree of atmospheric distortion 870. Adaptiveoptics systems may include one or more deformable mirrors 812 that areadjustable by actuators 872, 874. The actuators 872, 874 may adjust theshape of the deformable mirrors 812 to compensate for the opticalaberration caused by the atmospheric distortion 870. The photons maytravel to the rest of the components 890 in the apparatus 801 as shownin FIG. 1A. The apparatus 801 may further include a wavefront sensor892, which may read the received photons, calculate the appropriateadaptive corrections, and communicate them to the actuators 872, 874.The distortion having been reduced or corrected, the resultant signalsreceived by the optical detectors 130 a, 130 b may be significantly moreaccurate.

The adaptive optics system may rely on the light reflected by thesurface of the object being measured, artificial illumination of theobject, or separate guide star illumination. An artificial source 880may be used to provide illumination. The artificial source 880 mayinclude global illumination of the portion of the object 1 desired to beimaged. In another example, the artificial source 880 may include aguide star, which is an artificial image used to provide a referencepoint for the apparatus 801. In aspects where a guide star is used inoperation, simultaneous field measurements from a pixelated array ormultiple sensors may provide a reference source for local vibration oras a reference noise source.

Many imaging applications with a large distance between the object andthe sensor may see significant degradation in the capability of thetechnology to acquire acoustic information because of atmosphericturbulence. For the illustrative example of observing resolvedsatellites, it may be appreciated that spatial information for each ofthe satellite subsystems will be physically blurred. These subsystemsmay be components such as the spacecraft solar arrays, antennae, orappendages. The application of either deconvolution or adaptive opticscorrection techniques either separately or combined will restore theimages such that applications such as modal analysis may be implementedto measure such effects as the vibrational modes of solar panels inducedby such phenomena as tracking articulation or thermal shock from earthshadowing. For non-resolved cases, the use of image correction mayperform such necessary functions as sharpening the system point spreadfunction to improve photon sampling statistics and offer improved imagecontrast for separating closely spaced objects.

FIG. 9 is a schematic block diagram showing a remote sensing apparatus900 with a polarization fiber switch 920, in accordance with a fourthexemplary embodiment of the present invention. The apparatus 900includes collection optics 110 directing photons from an object 1. Thephotons are directed into a fiber optic cable 910, which is in opticalcommunication with a polarization fiber switch 920 (fiber switch 920).The fiber switch 920 is switchable between a first and secondpolarization state. In the first polarization state, photons having thefirst polarization state 922 a are directed through the polarizationfiber switch. In the second polarization state, photons having thesecond polarization state 922 b are directed through the polarizationfiber switch. An optical detector 130 is in optical communication withthe fiber switch 920. At least one processor 140 is in communicationwith the optical detector 130. The at least one processor 140: receivesa signal from the optical detector, wherein a first portion of thesignal corresponds to the photons in the first polarization state 922 a,and a second portion of the signal corresponds to the photons in thesecond polarization state 922 b; calculates, for a segment of thesignal, a difference of the first and second portions of the signals, asum of the first and second portions of the signals, and a ratio of thedifference to the sum; and generates, for a plurality of segments, asignal corresponding to a sequential output of the ratio for eachsegment, wherein the signal is indicative of an acoustic signature of anobject being sensed.

The fiber optic cable 910 may be a single cable or a plurality of cablesas required by the implementation of the apparatus 900, the spectrumbeing imaged, and any other relevant factors. The fiber switch 920 maybe a switch that can switch the incoming signal quickly between twoorthogonal polarization states, for instance, two orthogonal linearpolarization states. This may allow the photons directed to the fiberswitch 920 to be separated into the two orthogonal polarization stateswhen the fiber switch 920 switches states. When the fiber switch 920 isin the first polarization state, only photons in the first polarizationstate 922 a are allowed to propagate through. When the fiber switch 920is in the second polarization state, only photons in the secondpolarization state 922 b are allowed to propagate through.

The photons in the first and second polarization states 922 a, 922 b mayarrive at the optical detector 130 at different times. For instance, ifthe fiber switch 920 switches rapidly back and forth between the firstand second polarization states, then photons in the first polarizationstate 922 a may arrive at the optical detector 130 first, followed byphotons in the second polarization state 922 b, repeating over and over.The rate at which the fiber switch 920 oscillates between the first andsecond polarization states may be at least twice than the desiredsampling rate of the apparatus to allow both polarization states to besampled with enough frequency. The optical detector 130 may detect thephotons as they reach the optical detector 130. The processor 140 maydistinguish the polarization state of the signal from the opticaldetector 130 based on when the photons reached the optical detector 130.This may allow the apparatus 900 to detect the DoLP of the object usingonly a single optical detector 130, which may allow the apparatus 900 tobe more compact in design.

The apparatus 900 may include any combination of the hardware componentsdescribed relative to FIGS. 1A-8, above, including the collection optics110, sound transducer 160, an illumination source, adaptive opticscorrections, computer processor components, and the like.

It should be emphasized that the above-described embodiments of thepresent disclosure, particularly, any “preferred” embodiments, aremerely possible examples of implementations, merely set forth for aclear understanding of the principles of the disclosure. Many variationsand modifications may be made to the above-described embodiment(s) ofthe disclosure without departing substantially from the spirit andprinciples of the disclosure. Particularly, any aspect of thisdisclosure may be used by, combined with, or added onto any other aspectof this disclosure. All such modifications and variations are intendedto be included herein within the scope of this disclosure and thepresent disclosure and protected by the following claims.

What is claimed is:
 1. A photo-acoustic polarimetric remote sensingapparatus, comprising: collection optics directing photons; a polarizingbeam splitter having first and second pathways, wherein photons withinthe first and second pathways have first and second polarization states,respectively; a first optical detector located in the first pathway; asecond optical detector located in the second pathway; and at least oneprocessor in communication with the first and second optical detectors,wherein the at least one processor: receives first and second signalsfrom the first and second optical detectors, respectively, wherein atemporal sample rate of the received first and second signals is atleast the Nyquist rate; calculates, for a segment of the first andsecond signals, a difference of the first and second signals, a sum ofthe first and second signals, and a ratio of the difference to the sum;and generates, for a plurality of segments, a signal corresponding to asequential output of the ratio for each segment, wherein the signal isindicative of an acoustic signature of an object being sensed.
 2. Theapparatus of claim 1, wherein at least one surface of the collectionoptics is adjustably deformable to compensate for atmospheric distortionof the photons.
 3. The apparatus of claim 2, further comprising a guidestar to illuminate the object being sensed.
 4. The apparatus of claim 1,wherein the at least one processor is further configured to perform oneoperation from the set of: principal component analysis, Kalmanfiltering, and Bayesian estimation on the received first and secondsignals.
 5. The apparatus of claim 1, wherein when the temporal samplerate of the detected photons falls below the Nyquist limit, the at leastone optical detector resamples the detected photons, and first andsecond signals corresponding to the resampled photons is averaged withthe first and second signals corresponding to the first sampled photons.6. The apparatus of claim 1, wherein the at least one processor isfurther configured to apply at least one filter to the received signalsfrom the set of: moving averages, Savitsky-Golay, and Weinerdeconvolution.
 7. A photo-acoustic, polarimetric method of remotelysensing an object, comprising the steps of: collecting photons from theobject; directing the photons down first and second pathways, whereinphotons within the first pathway have a first polarization state andphotons within the second pathway have a second polarization state;detecting photons in the first and second pathways using at least oneoptical detector, wherein the photons in the first polarization stateproduce a first signal and the photons in the second polarization stateproduce a second signal; receiving, with at least one processor incommunication with the at least one optical detector, a first signal anda second signal corresponding to the photons in the first pathway andsecond pathway, respectively, wherein a temporal sample rate of thereceived first and second signals is at least the Nyquist rate;determining, with the at least one processor and for a segment of thefirst and second signals, a difference of the first and second signals,a sum of the first and second signals, and a ratio of the difference tothe sum; and generating, for a plurality of segments, a signalcorresponding to a sequential output of the ratio for each segment,wherein the signal is indicative of an acoustic signature of the object.8. The method of claim 7, further comprising the step of applyingfrequency domain decomposition to the generated signal to detectspectral components.
 9. The method of claim 7, further comprising: at alater point in time, repeating the steps of receiving a first and secondsignal corresponding to photons in the first pathway and second pathway,respectively, and determining a difference of the first and secondsignals, a sum of the first and second signals, and a ratio of thedifference to the sum; and calculating a cross-spectrum of theearlier-determined ratio and the later-determined ratio.
 10. The methodof claim 7, further comprising the step of performing one from the setof principal component analysis, Kalman filtering, and Bayesianestimation on the received first and second signals.
 11. The method ofclaim 7, wherein when the temporal sample rate of the detected photonsfalls below the Nyquist limit, the at least one optical detectorresamples the detected photons, and first and second signalscorresponding to the resampled photons is averaged with the first andsecond signals corresponding to the first sampled photons.
 12. Themethod of claim 7, further comprising the step of applying at least onefilter to the received signals from the set of: moving averages,Savitsky-Golay, and Weiner deconvolution.
 13. The method of claim 7,further comprising the step of improving human perceptibility of thegenerated signal by applying at least one from the set of: Bayesianestimation, feedforward operations, and feedback operations.
 14. Themethod of claim 7, further comprising the step of beam forming thereceived signals using at least one from the set of: averaging, summing,or nulling, wherein the received signals are spatially separated. 15.The method of claim 7 further comprising the steps of: measuring avibration signature of each pixel of the at least one €optical detector;and removing Fourier power components from the measured vibrationsignature.
 16. The method of claim 7, further comprising the step ofperforming a modal imaging analysis on the received first and secondsignals.
 17. The method of claim 16, wherein discovered modes areindicated by generating an additional signal corresponding to thediscovered modes, wherein the additional signal comprises at least onefrom the set of: false-color enhancement, motion amplification, anddecimated rate displays.
 18. The method of claim 7, further comprisingthe step of estimating the effective mass of the object based on aproduct of the generated signal and at least one from the set of: aknown input force, a stiffness coefficient, and a dampening coefficient.19. A photo-acoustic polarimetric remote sensing apparatus, comprising:collection optics directing photons; an optical detector; amicro-polarizer array located on the optical detector, wherein themicro-polarizer array separates the photons into at least a firstpolarization state and a second polarization state; wherein a firstportion of the optical detector receives the photons in the firstpolarization state, and wherein a second portion of the optical detectorreceives the photons in the at least second polarization state; and atleast one processor in communication with the optical detector, whereinthe at least one processor: receives a signal from the optical detector,wherein a first portion of the signal corresponds to the photons in thefirst polarization state, and a second portion of the signal correspondsto the photons in the at least second polarization state; calculates,for a segment of the signal, a difference of the first and at leastsecond portions of the signals, a sum of the first and at least secondportions of the signals, and a ratio of the difference to the sum; andgenerates, for a plurality of segments, a signal corresponding to asequential output of the ratio for each segment, wherein the signal isindicative of an acoustic signature of an object being sensed.
 20. Theapparatus of claim 19, wherein the micro-polarizer array comprises a 0°,45°, 90°, and 135° linear polarizer for each pixel of the opticaldetector.
 21. A photo-acoustic polarimetric remote sensing apparatus,comprising: collection optics directing photons; a polarization fiberswitch in optical communication with the collection optics, wherein thepolarization fiber switch is switchable between a first and secondpolarization state, wherein in the first polarization state, photonshaving the first polarization state are directed through thepolarization fiber switch, and wherein in the second polarization state,photons having the second polarization state are directed through thepolarization fiber switch; an optical detector in optical communicationwith the polarization fiber switch; and at least one processor incommunication with the optical detector, wherein the at least oneprocessor: receives a signal from the optical detector, wherein a firstportion of the signal corresponds to the photons in the firstpolarization state, and a second portion of the signal corresponds tothe photons in the second polarization state; calculates, for a segmentof the signal, a difference of the first and second portions of thesignals, a sum of the first and second portions of the signals, and aratio of the difference to the sum; and generates, for a plurality ofsegments, a signal corresponding to a sequential output of the ratio foreach segment, wherein the signal is indicative of an acoustic signatureof an object being sensed.